Special Issue on: Advances of Smart Industrial Informatics and Operations Research
摘要截稿:
全文截稿: 2020-05-31
影响因子: 3.424
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 2区
• 小类 : 计算机:跨学科应用 - 2区
• 小类 : 工程:工业 - 2区
• 小类 : 运筹学与管理科学 - 2区
Overview
The new generation of Industrial Informatics Technology, including the Internet of Things (IoT), Cloud Computing, Big Data and Artificial Intelligence/Deep Learning, is substantially expanding the frontiers of smart industries and industry 4.0 (the fourth industrial revolution). Meanwhile, Operations Research (OR) methodologies have long been acknowledged to be a key driver of effective automated decision support in many industrial systems. The pervasive sensing capabilities of industrial IoT systems give rise to the explosive generation of huge and diverse volumes of big data, which is the new “oil” that should be effectively incorporated in and smartly utilized by the OR models to assist optimal decision-making for industrial applications.
On the flip side, the world of big data includes a rich and complex set of cross-media content, including text, images, video, audio, and graphics. This calls for the next generation of online, elastic and evolutionary data analytics technologies, machine learning and OR models, which can exploit heterogeneous big data and make decisions more intelligently in a (near) real-time manner. Cloud Computing, Big Data and Artificial Intelligence/Deep Learning lay a solid foundation for handling such big data. Cloud and network analytics can harness the immense stream of operational data from clouds and networks and can perform analytics processing to improve reliability, configuration, performance, fault and security management. In particular, we see an increasing trend towards using statistical analysis and machine learning to improve operations and management of industrial IoT systems and networks. This promising area can generate concrete impact on the productivity and sustainability of interconnected industries with economics of scale in the future cyber-physical world. Apart from technological efficiencies, OR models are the basis for analyzing big data and extracting the insightful information to make more accurate and timely decisions.
This special issue aims to seek and disseminate recent theoretical and methodological developments, significant technical applications, case studies and survey results in areas of advanced OR models integrating industrial informatics and machine learning techniques for next generation manufacturing and industry 4.0. Specific topics of interest include, but are not limited to the following:
Architecture, interoperability and standard for industry 4.0
Emerging sensing technologies of IoT for industry 4.0
IoT-enabled industrial process monitoring and control
Scheduling and process optimization for industry 4.0
Design for manufacturing, robustness design, reverse engineering
Service systems including energy, environment and communication
Smart network design and transportation
Smart healthcare systems design
Smart inventory control systems design
Revenue management in industrial value chain
Cloud based big data and artificial intelligence for industrial informatics applications
Data mining, statistical modeling, and machine learning for smart industrial informatics
Data centric management of software defined networks
Anomaly detection and prediction
Theoretical and empirical performance model for big data applications
Assessing the impact of BDA on performance measurement systems in operation management and supply chain